The present invention relates, generally, to inspection apparatus, and, in particular, to automatic optical inspection apparatus for on-line inspection of articles, having self-programming capability.
Quality assurance by on-line inspection has until recently been the province of human inspectors stationed at key points along a production line for the purpose of detecting and removing defective specimens of the product. Although the skill levels usually required are not high, the task requires attention and diligence of a high order. From a cost standpoint, quality inspection requires large man-hour expenditures to accomplish tasks which are highly routine.
Many industrial products are inspected visually during the manufacturing process to determine if a certain operation has been performed properly. Characteristics being inspected include: shape, size, presence/absence of holes and other details; color, surface finish, gloss, code marks and other character recognition features; completeness, presence of a sub-part; orientation, label placement, proper label, proper product, flaws, defects, drips, spillage and particles.
Some specific examples of the above include the color of tomato ketchup, contaminants in I.V. saline solutions, label placement on liquid detergents, orientation of semiconductor die and lead frames, completion of mesh etching, proper pharmaceutical package for the product contained therein, loose debris and defects in beverage bottles and uniform coating of magnetic tape. These are all examples where the inspection task is now being performed by one or more persons on each production line and where automation would be welcomed.
Attempts to reduce the amount of human labor involved have followed several paths or combinations of them. Most simple, perhaps, is to reduce the quality level standard required to be met or to reduce the number of units actually inspected; i.e., statistical sampling. Either of these approaches affects an immediate reduction in labor costs, but with a corresponding loss in level of confidence that the end product will meet the desired quality standards. Of the two, "sampling" techniques, whereby a statistically significant percentage of each production run is selected for analysis on a random basis, offer the possibility of maintaining high overall quality levels, but at the risk of an occasional inferior product being passed into the stream of commerce.
For many low-risk product applications, this risk is acceptable since the few inferior products which do get past inspection cause slight, if any, damage even to the maker's reputation. For other applications, however, such as dangerous drugs or flammable liquids, the absence of an appropriate warning label may lead to disastrous consequences. In such cases, inspection of less than 100 percent of the product is foolhardy.
Efforts to provide inspection of entire production runs without incurring the high labor cost attendent to human inspection, and without the errors which occur when fatique sets in, attention flags, and diligence wanes, have led to the design of a variety of mechanical substitutes for the human inspector. Typical of such machines are those which detect weight, fill-level or presence of the product.
Unfortunately, when more data needs to be analyzed in order to conduct a proper inspection, the cost of equipment can increase astronomically. Moreover, since such data analysis requires a high level of sophistication in order to even approximate the rapid and perhaps subconscious routines which a human inspector's brain and sense follow, the labor involved in applying equivalent mechanical means to the specific task at hand frequently exceeds the cost of the former labor-intensive inspection method. As such, only those applications having the highest volumes can justify the equipment and preparatory operating cost.
Substitution of machine labor for human labor involves initially analyzing the tasks which are involved in making quality inspection decisions. The human inspection task can be defined in a very general way as including illumination of an object, visual perception of the object followed by retinal pre-processing, forebrain data handling, memory for storage of relevant inspection standards, comparision of the detected object with the stored inspection standards, decision making based upon the results of the comparison with stored standards, and determination and execution of an appropriate action in response to the decision.
Electronic analogs of each of these sub-tasks exist and have been employed in simplified forms for a large number of inspection tasks employing dedicated apparatuses, wherein all, or some, of the elements are combined in to an equipment intended for a specific application.
The electronic analogs include: illumination, as before, with objective and imaging optics; sensors which replace the eye of the human operator; analog or digital signal processing or both corresponding to forebrain data handling in a human operator, digital memory means corresponding to the human operator's memory; digital comparators and correlation circuitry corresponding to comparison of the observed features with the inspection standards; and output actuators corresponding to the action taken by the human operator when a defect is discovered.
Adaptive pattern recognition equipment can be employed to good advantage in many applications, but the cost and complexity of the equipment is high in comparison with the results desired. Moreover, for example, when allowance for tolerances on product dimensions are sought to be incorporated in the inspection equipment, the programming becomes extremeley complex.
With the advent of the general purpose, digital, programmable microprocessor, the logic, evaluation and comparison tasks performed by a human inspector could be duplicated within the memory and arithmetic logic unit of the microprocessor. However, for even the simplest measurements, a high level of skill is required to design the required application program by which a microprocessor-based inspection apparatus can be implemented. The result is that the cost of programming can easily exceed the benefit gained by automation.
The high-skill/high-cost labor required to program the microprocessor results in a high overall application cost, even though equipment costs may be reduced by the economies of scale which result when a general purpose machine can be substituted for dedicated machines tailored to each application.
For a conventional pattern recognition system, an entire field of data is obtained which covers and overlaps the edges of the object under inspection, and, comparisons are performed over the entire data field. For the most part, however, only certain features of the object actually need to be considered in order to determine whether any given object characteristic falls within the standard for acceptability. Thus, a label inspection station could be satisfactorily realized by sampling only the four corners of a square label, for example, thereby determining the acceptability of its position and angular displacement of the label. By extracting only the salient points from the field of available data, and making a decision solely upon these salient points, the cost of equipment, and the data throughput rate can both be optimized.
Finally, a severe drawback of conventional pattern recognition equipment lies in the fact that the operator is forced to operate "blind" with respect to the programming details associated with a particular, machine performance. For example, the inspection station operator has little control over or knowledge of the information concerning location tolerance limits which have been programmed in the machine and, accordingly, has little confidence in its performance. To remedy this, the operator could be a skilled programmer who understands and appreciates the form and content of the data which have been input into the equipment. However, this results in the overall inspection station hourly operating cost being raised back toward the cost of inspection by the original, human inspector.